👀 Views: 0 💬 Answers: 1 📅 Created: 2025-07-05

r dplyr dataframe R

I'm reviewing some code and I'm building a feature where Hey everyone, I'm running into an issue that's driving me crazy..... Quick question that's been bugging me - I am trying to create a new column in a data frame using `dplyr::mutate()` that involves list-columns, but I'm encountering some unexpected behavior. I have a data frame containing a list-column with numeric vectors, and I want to calculate the mean of each vector and store the results in a new column. Here’s what my data frame looks like: ```r library(dplyr) # Sample data frame my_data <- data.frame( id = 1:3, values = I(list(c(1, 2, 3), c(4, 5), c(6, 7, 8, 9))) ) ``` When I try to use `mutate()` like this: ```r my_data <- my_data %>% mutate(mean_values = sapply(values, mean)) ``` I get the following warning message: ``` Warning message: In sapply(values, mean) : argument is not numeric or logical: returning NA ``` It seems like the `sapply()` is not correctly handling the list-column, and instead of calculating the means, it returns `NA` values. I also attempted using `lapply()` like this: ```r my_data <- my_data %>% mutate(mean_values = lapply(values, mean)) ``` But that just gives me a list in the new `mean_values` column, which is not what I need. I want to have a numeric vector instead of a list. I looked through the `dplyr` documentation but couldn't find a clear example of how to handle this case. Is there a proper way to achieve this using `dplyr`? Any suggestions or best practices on dealing with list-columns in `mutate()` would be greatly appreciated! For context: I'm using R on macOS. Has anyone else encountered this? Is there a better approach? I'm working in a Windows 10 environment. I'm working with R in a Docker container on Windows 10. Hoping someone can shed some light on this.